Tag: visualisation

Sometimes you just have to plot more than one dataset on the same chart, but you might have a complex data table with some “collections” of single-values and some collections of multiple values. Here I’ve put together an example from something I’ve been working on recently. Once your back-end queries (SQL or whatever) are written and your templates convert those data into basic HTML tables, you can plot then straight to SVG/D3 without much extra work.

Nearly all of that extra work is around adding appropriate classes to cells to distinguish columns and collections of columns. The rest is to extract those cells out again and decide which should be plotted together.

In this example, tabs and table headings belong to classes “collection_#” “a_c#” where the collection_# identifies a set of columns to be displayed together and the a_c# identifies the (links for the) columns themselves. Collections with multiple columns therefore have a single collection class but contain more than one a_c# class.

Next each table tbody td data cell belongs to a c# class, one for each column. Each one is also uniquely identified by a td#_<date> which allows hovers on the table cell to highlight the SVG data point and vice versa. Next each cell contains a span with a “val” class (more on that in the next post).

SVG paths may now be built for each column. Clicks on table-headings and tabs are able to examine which columns co-display because they belong in the same collection and then scale and plot them appropriately.

Note that the first and last tabs in this example plot single lines to demonstrate mixed collections in action. The middle two tabs have two lines each but there’s no reason why you couldn’t have more (although there are only seven colours listed at the moment).

I’ve been tinkering with D3js on and off for a couple of months now, purely for generating simple, inline charts in web pages, made from data already dumped into HTML tables. Doing this is easier than building, caching and referencing external bitmap (PNG, GIF or whatever) images with Gnuplot or GD::Graph and also simpler than building bitmap images and serving them base64 encoded inline with <img alt=”” src=”data:…” />.

Using jQuery (or similar) to extract data from an already-present HTML table means there’s almost no code required whenever you want to add and plot a new column that someone might want to report on. Pushing all the work to the client should also mean slightly lighter server loads, though granted it’s already done the heavy lifting during the query to generate the table.

I’ve used examples from a number of sources, mostly from over on the d3js.org website itself and Mike Bostock’s inspiring example gallery. Plus the ever useful jQuery and jQueryUI libraries.

The result is a tabbed (with a jqueryui-themed unordered list) report based on a data table below. Clicking on either a tab or a table heading (all except the date) will animate and redraw the chart above. The data are collected using a jQuery selector on column classes in each.